






"""simple docstring"""





from pathlib import Path
from typing import List

from transformers import is_torch_available, is_vision_available
from transformers.testing_utils import get_tests_dir, is_tool_test
from transformers.tools.agent_types import AGENT_TYPE_MAPPING, AgentAudio, AgentImage, AgentText


if is_torch_available():
  import torch

if is_vision_available():
  from PIL import Image


_SCREAMING_SNAKE_CASE   :							List[Any]          =		['''text''', '''image''', '''audio''']







def 	lowerCamelCase__			(				_lowerCamelCase			:						List[str]					) ->							Dict:
  lowerCamelCase_       	=		[]

  for input_type in input_types:
    if input_type == "text":
      inputs.append('Text input'					)
    elif input_type == "image":
      inputs.append(
          Image.open(Path(get_tests_dir('fixtures/tests_samples/COCO'					)					) / '000000039769.png'					).resize((512, 512)					)					)
    elif input_type == "audio":
      inputs.append(torch.ones(3000					)					)
    elif isinstance(_lowerCamelCase						,							_lowerCamelCase					):
      inputs.append(create_inputs(_lowerCamelCase					)					)
    else:
      raise ValueError(F'''Invalid type requested: {input_type}'''					)

  return inputs







def 	lowerCamelCase__			(				_lowerCamelCase			:						List					) ->							str:
  lowerCamelCase_       	=		[]

  for output in outputs:
    if isinstance(_lowerCamelCase						,							(str, AgentText)					):
      output_types.append('text'					)
    elif isinstance(_lowerCamelCase						,							(Image.Image, AgentImage)					):
      output_types.append('image'					)
    elif isinstance(_lowerCamelCase						,							(torch.Tensor, AgentAudio)					):
      output_types.append('audio'					)
    else:
      raise ValueError(F'''Invalid output: {output}'''					)

  return output_types






@is_tool_test
class 	a		:






    def   UpperCamelCase			(			self	:				str   )	->						Dict:
      self.assertTrue(hasattr(self.tool			,		'inputs'   )   )
      self.assertTrue(hasattr(self.tool			,		'outputs'   )   )

      lowerCamelCase_       	=		self.tool.inputs
      for _input in inputs:
        if isinstance(_input			,		__SCREAMING_SNAKE_CASE   ):
          for __input in _input:
            self.assertTrue(__input in authorized_types   )
        else:
          self.assertTrue(_input in authorized_types   )

      lowerCamelCase_       	=		self.tool.outputs
      for _output in outputs:
        self.assertTrue(_output in authorized_types   )






    def   UpperCamelCase			(			self	:				Optional[Any]   )	->						List[str]:
      lowerCamelCase_       	=		create_inputs(self.tool.inputs   )
      lowerCamelCase_       	=		self.tool(*__SCREAMING_SNAKE_CASE   )

      # There is a single output
      if len(self.tool.outputs   ) == 1:
        lowerCamelCase_       	=		[outputs]

      self.assertListEqual(output_types(__SCREAMING_SNAKE_CASE   )			,		self.tool.outputs   )






    def   UpperCamelCase			(			self	:				Tuple   )	->						Optional[int]:
      self.assertTrue(hasattr(self.tool			,		'description'   )   )
      self.assertTrue(hasattr(self.tool			,		'default_checkpoint'   )   )
      self.assertTrue(self.tool.description.startswith('This is a tool that'   )   )






    def   UpperCamelCase			(			self	:				str   )	->						List[str]:
      lowerCamelCase_       	=		create_inputs(self.tool.inputs   )
      lowerCamelCase_       	=		self.tool(*__SCREAMING_SNAKE_CASE   )

      if not isinstance(__SCREAMING_SNAKE_CASE			,		__SCREAMING_SNAKE_CASE   ):
        lowerCamelCase_       	=		[outputs]

      self.assertEqual(len(__SCREAMING_SNAKE_CASE   )			,		len(self.tool.outputs   )   )

      for output, output_type in zip(__SCREAMING_SNAKE_CASE			,		self.tool.outputs   ):
        lowerCamelCase_       	=		AGENT_TYPE_MAPPING[output_type]
        self.assertTrue(isinstance(__SCREAMING_SNAKE_CASE			,		__SCREAMING_SNAKE_CASE   )   )






    def   UpperCamelCase			(			self	:				Any   )	->						Optional[Any]:
      lowerCamelCase_       	=		create_inputs(self.tool.inputs   )

      lowerCamelCase_       	=		[]

      for _input, input_type in zip(__SCREAMING_SNAKE_CASE			,		self.tool.inputs   ):
        if isinstance(__SCREAMING_SNAKE_CASE			,		__SCREAMING_SNAKE_CASE   ):
          _inputs.append([AGENT_TYPE_MAPPING[_input_type](_input   ) for _input_type in input_type]   )
        else:
          _inputs.append(AGENT_TYPE_MAPPING[input_type](_input   )   )

        # Should not raise an error
      lowerCamelCase_       	=		self.tool(*__SCREAMING_SNAKE_CASE   )

      if not isinstance(__SCREAMING_SNAKE_CASE			,		__SCREAMING_SNAKE_CASE   ):
        lowerCamelCase_       	=		[outputs]

      self.assertEqual(len(__SCREAMING_SNAKE_CASE   )			,		len(self.tool.outputs   )   )












"""simple docstring"""





def 	lowerCamelCase__			(				_lowerCamelCase			:						float						,							_lowerCamelCase			:						float					) ->							float:

  if density <= 0:
    raise ValueError('Impossible fluid density'					)
  if bulk_modulus <= 0:
    raise ValueError('Impossible bulk modulus'					)

  return (bulk_modulus / density) ** 0.5


if __name__ == "__main__":
  import doctest

  doctest.testmod()




